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Add convolve for DiscreteNonParametric #1523

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Add convolve for DiscreteNonParametric #1523

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15ec552
Add convolve for DiscreteNonParametric
iampritishpatil Mar 22, 2022
62331ac
Update src/convolution.jl
iampritishpatil Mar 23, 2022
735a33f
Use Set, instead of splatting.
iampritishpatil Mar 23, 2022
1c05992
Fix type stability of elements.
iampritishpatil Mar 23, 2022
af9bc65
Apply suggestions from code review
iampritishpatil Mar 23, 2022
4b27856
Added a test set.
iampritishpatil Mar 23, 2022
f85407a
minor rename for consistency
iampritishpatil Mar 23, 2022
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15 changes: 15 additions & 0 deletions src/convolution.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@ and one of
* [`NegativeBinomial`](@ref)
* [`Geometric`](@ref)
* [`Poisson`](@ref)
* [`DiscreteNonParametric`](@ref)
* [`Normal`](@ref)
* [`Cauchy`](@ref)
* [`Chisq`](@ref)
Expand Down Expand Up @@ -47,6 +48,20 @@ end
convolve(d1::Poisson, d2::Poisson) = Poisson(d1.λ + d2.λ)



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Suggested change

function convolve(d1::DiscreteNonParametric, d2::DiscreteNonParametric)
support_conv = collect(Set(s1 + s2 for s1 in support(d1), s2 in support(d2)))
sort!(support_conv) #for fast index finding below
probs1 = probs(d1)
probs2 = probs(d2)
p_conv = zeros(Base.promote_eltype(probs1, probs2), length(support_conv))
for (s1, p1) in zip(support(d1), probs(d1)), (s2, p2) in zip(support(d2), probs(d2))
idx = searchsortedfirst(support_conv, s1+s2)
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p_conv[idx] += p1*p2
end
DiscreteNonParametric(support_conv, p_conv,check_args=false)
end

# continuous univariate
convolve(d1::Normal, d2::Normal) = Normal(d1.μ + d2.μ, hypot(d1.σ, d2.σ))
convolve(d1::Cauchy, d2::Cauchy) = Cauchy(d1.μ + d2.μ, d1.σ + d2.σ)
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21 changes: 21 additions & 0 deletions test/convolution.jl
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Expand Up @@ -66,6 +66,27 @@ using Test
@test d3 isa Poisson
@test d3.λ == 0.5
end

@testset "DiscreteNonParametric" begin
d1 = DiscreteNonParametric([0,1],[0.5,0.5])
d2 = DiscreteNonParametric([1,2],[0.5,0.5])
d_eps= DiscreteNonParametric([-1* eps(Float64),0.0,eps(Float64),1.0],[1//4,1//4,1//4,1//4])
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Maybe use

Suggested change
d_eps= DiscreteNonParametric([-1* eps(Float64),0.0,eps(Float64),1.0],[1//4,1//4,1//4,1//4])
d_eps= DiscreteNonParametric([prevfloat(0.0),0.0,nextfloat(0.0),1.0], fill(1//4, 4))

d10= DiscreteNonParametric(collect(1:10)//10,ones(Int,10)//10)
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d10= DiscreteNonParametric(collect(1:10)//10,ones(Int,10)//10)
d10= DiscreteNonParametric(1//10:1//10:1, fill(1//10, 10))


d_int_simple = @inferred(convolve(d1, d2))
@test d_int_simple isa DiscreteNonParametric
@test support(d_int_simple) == [1,2,3]
@test probs(d_int_simple) == [0.25,0.5,0.25]

d_rat = convolve(d10, d10)
@test support(d_rat)[1] == 1//5
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I guess this could be made more precise?

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@test support(d_rat)[1] == 1//5
@test support(d_rat) == 1//5:1//10:2

@test probs(d_rat)[1] == 1//100

d_float_supp = convolve(d_eps, d_eps)
@test support(d_float_supp)[3] == 0.0
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I think this will be

Suggested change
@test support(d_float_supp)[3] == 0.0
@test support(d_float_supp) == [2 * prevfloat(0.0), prevfloat(0.0), 0.0, nextfloat(0.0), 2 * nextfloat(0.0), 1.0, 2.0]

since numerically prevfloat(0.0) + 1 = 1 = nextfloat(0.0) + 1.

@test probs(d_float_supp)[3] == 3//16
end

end

@testset "continuous univariate" begin
Expand Down